{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["2"],"submitter":["Kim MM"],"funding":["Natural Sciences and Engineering Research Council (NSERC) of Canada"],"pubmed_abstract":["Substitution of serum and other clinically incompatible reagents is requisite for controlling product quality in a therapeutic cell manufacturing process. However, substitution with chemically defined compounds creates a complex, large-scale optimization problem due to the large number of possible factors and dose levels, making conventional process optimization methods ineffective. We present a framework for high-dimensional optimization of serum-free formulations for the expansion of human hematopoietic cells. Our model-free approach utilizes evolutionary computing principles to drive an experiment-based feedback control platform. We validate this method by optimizing serum-free formulations for first, TF-1 cells and second, primary T-cells. For each cell type, we successfully identify a"],"journal":["Communications biology"],"pagination":["48"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6358607"],"repository":["biostudies-literature"],"pubmed_title":["On-demand serum-free media formulations for human hematopoietic cell expansion using a high dimensional search algorithm."],"pmcid":["PMC6358607"],"pubmed_authors":["Kim MM","Audet J"],"additional_accession":[]},"is_claimable":false,"name":"On-demand serum-free media formulations for human hematopoietic cell expansion using a high dimensional search algorithm.","description":"Substitution of serum and other clinically incompatible reagents is requisite for controlling product quality in a therapeutic cell manufacturing process. However, substitution with chemically defined compounds creates a complex, large-scale optimization problem due to the large number of possible factors and dose levels, making conventional process optimization methods ineffective. We present a framework for high-dimensional optimization of serum-free formulations for the expansion of human hematopoietic cells. Our model-free approach utilizes evolutionary computing principles to drive an experiment-based feedback control platform. We validate this method by optimizing serum-free formulations for first, TF-1 cells and second, primary T-cells. For each cell type, we successfully identify a","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019","modification":"2026-05-07T06:24:38.71Z","creation":"2019-03-26T22:50:52Z"},"accession":"S-EPMC6358607","cross_references":{"pubmed":["30729186"],"doi":["10.1038/s42003-019-0296-7"]}}